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Lane Spline Generation Using Edge Detection Robust to Environmental Changes

외부 환경 변화에 강인한 에지 검출을 통한 차선의 스플라인 생성

  • Received : 2012.09.12
  • Accepted : 2012.11.12
  • Published : 2012.11.30

Abstract

Lane detection with the use of a camera is an essential task required for the development of advanced driving assistance system. In this paper, edges of the lane are generated by applying Canny's method. The edge detection usually makes different results for several environmental conditions depending on the clearness of lane quality, so that it sometimes causes wrong lane detection. Therefore, we propose robust algorithm to environmental changes that automatically adjusts parameter for edge detection and generates edges more stably. Based on the acquired edges, we finally generate the spline curve of lane by using Catmull Rom spline.

영상을 통한 차선검출은 지능형 주행보조장치의 향상을 위해 필수적인 작업이다. 이 논문에서는 차선의 에지를 Canny 방법을 사용하여 생성한다. Canny 방법은 환경 상태에 따라 결과가 달라진다. 노면 상태가 분명함의 여부에 따라 잘못된 차선 검출을 할 수 있다. 그래서 안전한 에지 검출을 위해 에지 검출시 파라미터를 자동 조절하여 환경 변화에 강인한 알고리즘을 제안한다. 획득한 에지 검출을 기반으로 Catmull Rom spline 을 사용하여 스플라인으로 차선을 생성한다.

Keywords

References

  1. J.‐W. Park, J.‐W. Lee, K.‐Y. Jhang, "The development of the new lane model on the image for the highly efficient lane detection system," The Korean Society of Automotive Engineers, vol.3, pp. 1115‐1120, 2002
  2. J. Goldbeck, B. Huertgen, "Lane detection and tracking by video sensors," JSAI International Conference on 1999, pp. 74-79, 1999
  3. J.‐S. An, T.‐S. Oh, I.‐H. Kim, "Development of lane detection system using vision sensor," The Korean Institute of Electrical Engineers, pp. 1911-1912, 2008
  4. Rafael C. Gonzalez, Richard E. Woods, "Digital image processing," Third Edition, Prentice Hall
  5. Y. Wang, D. Shen, E. K. Teoh "Lane detection using spline model," Image and vision computing v.22 no.4 , pp.269-280, 2004 https://doi.org/10.1016/j.imavis.2003.10.003
  6. Z.‐X. Li, S.‐W. Kim, "A multi‐thresholding approach improved with Otsu's method," Journal of the Institute of Electronics Engineers of Korea. v.43 no.5= no.311, pp. 29-37 , 2006
  7. Y. Wang, E. K. Teoh, D. Shen, "Lane detection and tracking using B Snake," Image and vision computing v.22 no.4, pp. 269-280, 2004 https://doi.org/10.1016/j.imavis.2003.10.003
  8. Assidiq Abdulhakam.AM. ; Khalifa Othman O. ; Islam Md. Rafiqul, "Real time lane detection for autonomous vehicles," Computer and Communication Engineering, pp. 82-88, May, 2008
  9. Xin Zhou, Xi‐yue Huang, "Multi lane line reconstruction for highway application with a signal view," Image and Graphics, pp. 35-38, 2004
  10. R. Labayrade, J. Douret, D. Aubert, "A multi‐model lane detector that handles road singularities," Intelligent Transportation Systems Conference, pp. 1143-1148, 2006
  11. J.‐W. Lee, S.‐W. Lee, "A lane departure warning algorithm based on an edge distribution function," Transactions of Korea Society of Automotive Engineers, vol9 no.3, pp. 143-154, 2001
  12. J.‐W. Lee, U.‐K. Yi, "Lane departure warning system for intelligent vehicle," The Korean Society of Automotive Engineers, pp. 1271-1276, 2004
  13. B.‐C. Kwon, D.‐W. Shin, K.‐S. Park, "A study on a lane detection using robust edge detection for the road condition changes," Institute of Control, Robotics and System, FPB24, 2011